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ACStor: Optimizing Access Performance of Virtual Disk Images in Clouds

机译:ACStor:优化云中虚拟磁盘映像的访问性能

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摘要

In virtualized data centers, virtual disk images (VDIs) serve as the containers in virtual environment, so their access performance is critical for the overall system performance. Some distributed VDI chunk storage systems have been proposed in order to alleviate the I/O bottleneck for VM management. As the system scales up to a large number of running VMs, however, the overall network traffic would become unbalanced with hot spots on some VMs inevitably, leading to I/O performance degradation when accessing the VMs. In this paper, we propose an adaptive and collaborative VDI storage system (ACStor) to resolve the above performance issue. In comparison with the existing research, our solution is able to dynamically balance the traffic workloads in accessing VDI chunks, based on the run-time network state. Specifically, compute nodes with lightly loaded traffic will be adaptively assigned more chunk access requests from remote VMs and vice versa, which can effectively eliminate the above problem and thus improves the I/O performance of VMs. We implement a prototype based on our ACStor design, and evaluate it by various benchmarks on a real cluster with 32 nodes and a simulated platform with 256 nodes. Experiments show that under different network traffic patterns of data centers, our solution achieves up to performance gain on VM booting time and VM's I/O throughput, in comparison with the other state-of-the-art approaches.
机译:在虚拟数据中心中,虚拟磁盘映像(VDI)充当虚拟环境中的容器,因此其访问性能对于整体系统性能至关重要。已经提出了一些分布式VDI组块存储系统,以减轻VM管理的I / O瓶颈。但是,随着系统扩展到大量正在运行的VM,总的网络流量将不可避免地与某些VM上的热点变得不平衡,从而导致访问VM时I / O性能下降。在本文中,我们提出了一种自适应协作VDI存储系统(ACStor)来解决上述性能问题。与现有研究相比,我们的解决方案能够根据运行时网络状态动态平衡访问VDI块时的流量工作负载。具体而言,将为流量轻负载的计算节点自适应地分配来自远程VM的更多块访问请求,反之亦然,这可以有效消除上述问题,从而提高VM的I / O性能。我们基于ACStor设计实施原型,并在具有32个节点的真实集群和具有256个节点的模拟平台上通过各种基准对其进行评估。实验表明,与其他最新方法相比,在数据中心的不同网络流量模式下,我们的解决方案可在VM启动时间和VM I / O吞吐量方面实现性能提升。

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  • 作者单位

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

    Argonne National Laboratory, Lemont, IL;

    Chuzhou University, Chuzhou, China;

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

    Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China;

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  • 正文语种 eng
  • 中图分类
  • 关键词

    Collaboration; Peer-to-peer computing; Cloud computing; Degradation; Booting; Computational modeling; Containers;

    机译:协作;对等计算;云计算;降级;启动;计算建模;容器;

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